sf-business-data-export

Export Salesforce business data into business-readable Excel files from natural-language requests. Use when pull large Salesforce datasets beyond Report limi...

Before installing or running this skill: (1) expect to provide Salesforce credentials—either a logged-in Salesforce CLI environment or an auth JSON containing instance_url and access_token—because the scripts call `sf` and post SOAP requests; the registry metadata should explicitly declare that but does not. (2) Ensure the runtime has Python 3.9+, and the third-party packages (requests, openpyxl) installed or add an install step. (3) Run the scripts with a least-privileged, read-only Salesforce account when testing, and check any auth JSON files for secure storage (do not put long-lived access tokens in shared locations). (4) Review the code paths that call subprocess.run and requests.post to confirm no unexpected external endpoints or credential exfiltration will occur in your environment. (5) Prefer the maintainer add explicit requirements (required env vars or config paths), an install spec for dependencies, and clear documentation on how credentials are consumed so you can make an informed trust decision.

Type: OpenClaw Skill Name: sf-business-data-export Version: 1.0.0 The skill bundle is a specialized tool for exporting Salesforce data into business-readable Excel files. It contains a well-structured set of Python scripts (e.g., `export_soap_to_excel.py`, `collect_metadata.py`) that interact with the Salesforce CLI and SOAP API to perform data extraction, metadata retrieval, and validation. The instructions in `SKILL.md` provide a rigorous workflow for the AI agent, including error handling, polymorphic relationship management, and data validation. While the scripts contain hardcoded business logic and date filters (e.g., in `generate_layout_soql.py`), these appear to be specific configuration requirements for a particular business use case rather than malicious intent. The code uses safe subprocess execution patterns and standard libraries, with no evidence of data exfiltration to unauthorized endpoints or unauthorized persistence.